Inteligência computacional no mercado financeiro: uma revisão de técnicas para automação de operações

The field of financial applications has become increasingly complex and challenging, with non-linear and uncertain behaviors that change over time. Therefore, computational intelligence techniques, including neural networks, genetic algorithms and fuzzy logic, have gained prominence as promising sol...

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Bibliographic Details
Authors: Sobrinho, Guilherme Francisco Lima, Cavalcante, Rodolfo Carneiro
Format: article
Status:Published version
Publication Date:2023
Country:Brasil
Institution:Universidade Federal de Itajubá (UNIFEI)
Repository:Research, Society and Development
Language:Portuguese
OAI Identifier:oai:ojs.pkp.sfu.ca:article/41793
Online Access:https://rsdjournal.org/index.php/rsd/article/view/41793
Access Level:Open access
Keyword:Machine learning
Artificial neural networks
Genetic algorithms
Fuzzy logic.
Aprendizaje automático
Redes neuronales artificiales
Algoritmos genéticos
Lógica difusa.
Aprendizado de máquina
Redes neurais artificiais
Description
Summary:The field of financial applications has become increasingly complex and challenging, with non-linear and uncertain behaviors that change over time. Therefore, computational intelligence techniques, including neural networks, genetic algorithms and fuzzy logic, have gained prominence as promising solutions for automating decisions in the financial market. This article aims to explore recent studies that address the use of these techniques and discuss their applications, advantages and limitations. This is a narrative literature review, with an exploratory descriptive character. Literature collection was carried out in the Science Direct and Scopus databases, using keywords related to the theme. It is concluded that computational intelligence techniques have been shown to be capable of solving highly non-linear and time-varying problems, thus becoming an effective approach to automate operations in the financial market.